Klasifikasi Ulasan Pengguna Zoom Cloud Meetings Menggunakan Metode Information Gain dan Naïve Bayes Classifier

Aan Rohanah, Budi Arif Dermawan, Intan Purnamasari

Abstract


During the Covid-19 pandemic, ZOOM Cloud Meetings video conference application was felt to be of benefit. This is due to limited direct physical contact and all activities are carried out virtually from home. So that during the pandemic the ZOOM Cloud Meetings application was widely downloaded by various groups of people, and reaped various responses from users who complained on the Google Play Store. Complaints from user reviews can contain valuable information for application development. To obtain this information, user reviews of applications are classified based on the ISO 9126 category. ISO 9126 is one of the standards for evaluating software based on user satisfaction. The ISO standards used are functionality, efficiency, reliability, maintainability, portability, and usability. This study uses the CRISP-DM research methodology and for modeling in the classification applies the Naïve Bayes Classifier and Information Gain. Information Gain is used for word conversion and data transformation from categorical to numeric and to reduce data dimensions. Naïve Bayes is able to predict data to enter the classification class. Testing of the model applies manual and automatic k-fold cross validation testing. The results of the classification of the model in manual testing produce the best accuracy of 79% and the k-fold cross validation test is 80.51%. The existence of this accuracy value is expected to be a reference for developing the ZOOM Cloud Meetings application.

Keywords


CRISP-DM; Information Gain; ISO 9126; Naïve Bayes Classifier; Zoom Cloud Meetings

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DOI: http://dx.doi.org/10.32493/informatika.v6i2.10728

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Jurnal Informatika Universitas Pamulang (ISSN: 2541-1004 e-ISSN: 2622-4615)



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